1. Field of the Invention
The present invention relates to a method for identifying an object image by way of differentiating the object image from a background image. More particularly, the present invention relates to a method for identifying an object image in which a normal line direction of an outline portion of an object image is determined, and humans, vehicles, vegetables, etc. are classified and recognized in real time.
2. Prior Art
Conventionally, for the Texture Analysis, a Fourier transformation is utilized to analyze a two-dimensional grayscale picture. The Fourier transformation for the pictures is generally used to analyze the state of the surface of the object image shown in the picture.
In such an analysis, a picture is divided into square regions, a Fourier transformation is performed on the image data of the respective square regions, and crystal lattice direction, defects, etc. of the object image are analyzed based upon the obtained phase. In this case, a Fourier transformation is performed on the square regions; accordingly, the obtained phase becomes a vertical or horizontal directional vector of the square region. Accordingly, when, with this method, recognizing an object image with an un-specific form in the picture, a need for an even greater calculation to determine the normal line direction of the outline portion of the object image is required. Moreover, since the picture is divided into squares, depending on the position of the boundary of the picture and on the position where the square is arranged, the normal vector of the object image may not be obtained accurately. In order to reduce this disadvantage, a window function is applied on the outer part of the square region so as to lighten the weight. However, this results in that the calculation time becomes longer.
On the other hand, in an image processing in real time, when recognizing an indefinite shaped moving object image such as an individual, a differential image or a phase difference of the current image and the prior image is utilized. This prior method estimates the number of people, etc. based on the area of the region detecting a density difference more than a set level from the differential image, etc. However, in this method, since the recognition of the object images is determined based on an area size, it is unavoidable to incorrectly recognize an object image. For instance, it may recognize one large person as two people, and two small people moving in the same direction side by side as one person.